A taxonomy of latent structure assumptions for probability matrix decomposition models
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Publication:2259550
DOI10.1007/BF02296653zbMath1306.62478MaRDI QIDQ2259550
Michel Meulders, Paul De Boeck, Iven van Mechelen
Publication date: 4 March 2015
Published in: Psychometrika (Search for Journal in Brave)
Bayesian analysisdiscrete datadata augmentationmatrix decompositionpsychometricsposterior predictive check
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Constrained multilevel latent class models for the analysis of three-way three-mode binary data ⋮ Bayesian hierarchical classes analysis
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Cites Work
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- Probability matrix decomposition models
- Bayesianly justifiable and relevant frequency calculations for the applied statistician
- Estimating the dimension of a model
- Inference from iterative simulation using multiple sequences
- Posterior predictive \(p\)-values
- Estimating multiple classification latent class models
- Markov Chain Monte Carlo Convergence Diagnostics: A Comparative Review
- Sampling-Based Approaches to Calculating Marginal Densities
- Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
- The Calculation of Posterior Distributions by Data Augmentation
- Dealing With Label Switching in Mixture Models
- Computational and Inferential Difficulties with Mixture Posterior Distributions
- P Values for Composite Null Models
- Asymptotic Distribution of P Values in Composite Null Models
- Exploratory latent structure analysis using both identifiable and unidentifiable models
- Probabilistic Feature Analysis of Facial Perception of Emotions
- Probability matrix decomposition models and main-effects generalized linear models for the analysis of replicated binary associations.
- A new look at the statistical model identification
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